Removal of out-of-plane fluorescence for single cell visualization and quantification in cryo-imaging

Steyer, Grant J., Roy, Debashish, Salvado, Olivier, Stone, Meredith E. and Wilson, David L. (2009) Removal of out-of-plane fluorescence for single cell visualization and quantification in cryo-imaging. Annals of Biomedical Engineering, 37 8: 1613-1628. doi:10.1007/s10439-009-9726-x

Author Steyer, Grant J.
Roy, Debashish
Salvado, Olivier
Stone, Meredith E.
Wilson, David L.
Title Removal of out-of-plane fluorescence for single cell visualization and quantification in cryo-imaging
Journal name Annals of Biomedical Engineering   Check publisher's open access policy
ISSN 0090-6964
Publication date 2009-08-01
Year available 2009
Sub-type Article (original research)
DOI 10.1007/s10439-009-9726-x
Open Access Status Not Open Access
Volume 37
Issue 8
Start page 1613
End page 1628
Total pages 16
Place of publication New York, United States
Publisher Springer New York LLC
Language eng
Formatted abstract
We developed a cryo-imaging system, which alternates between sectioning (10–40 μm) and imaging bright field and fluorescence block-face image volumes with micron-scale-resolution. For applications requiring single-cell detection of fluorescently labeled cells anywhere in a mouse, we are developing software for reduction of out-of-plane fluorescence. In mouse experiments, we imaged GFP-labeled cancer and stem cells, and cell-sized fluorescent microspheres. To remove out-of-plane fluorescence, we used a simplified model of light-tissue interaction whereby the next-image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing an objective function on subtracted images. Tissue-specific attenuation parameters [μ T: heart (267 ± 47.6 cm−1), liver (218 ± 27.1 cm−1), brain (161 ± 27.4 cm−1)] were found to be within the range of estimates in the literature. “Next-image” processing removed out-of-plane fluorescence equally well across multiple tissues (brain, kidney, liver, etc.), and analysis of 200 microsphere images gave 97 ± 2% reduction of out-of-plane fluorescence. Next-image processing greatly improved axial-resolution, enabled high quality 3D volume renderings, and improved automated enumeration of single cells by up to 24%. The method has been used to identify metastatic cancer sites, determine homing of stem cells to injury sites, and show microsphere distribution correlated with blood flow patterns.
Keyword Image processing
Block face imaging
Fluorescence imaging
In vivo cellular imaging
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID C06 RR12463-01
Institutional Status Non-UQ

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